Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
#load data
df = px.data.gapminder()
df.head()
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
# YOUR CODE HERE
df_2007 = px.data.gapminder().query('year == 2007')
df_2007_new = df_2007.groupby('continent').sum()
df.head()
fig = px.bar(df_2007_new, x='pop', y =df_2007_new.index, color= df_2007_new.index, text_auto='.2s')
fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()
# YOUR CODE HERE
df_2007 = px.data.gapminder().query('year == 2007')
df_2007_new = df_2007.groupby('continent').sum()
df.head()
fig = px.bar(df_2007_new, x='pop', y =df_2007_new.index, color= df_2007_new.index, text_auto='.2s')
fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()
Add text to each bar that represents the population
# YOUR CODE HERE
df_2007 = px.data.gapminder().query('year == 2007')
df_2007_new = df_2007.groupby('continent').sum()
df.head()
fig = px.bar(df_2007_new, x='pop', y =df_2007_new.index, color= df_2007_new.index, text_auto='.2s')
fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(textposition='outside')
fig.show()
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
df_new = df.groupby(['year','continent']).sum().reset_index()
fig = px.bar(df_new, x='continent', y='pop', color= 'continent', text_auto= '.2s', animation_frame='year', range_y=[0,4000000000])
fig.show()
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
# YOUR CODE HERE
df_new = df.groupby(['year','country']).sum().reset_index()
fig = px.bar(df_new, x='country', y='pop', color= 'country', text_auto= '.2s', animation_frame='year', range_y=[0,1500000000])
fig.show()
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
# YOUR CODE HERE
df_new = df.groupby(['year','country']).sum().reset_index()
fig = px.bar(df_new, x='country', y='pop', color= 'country', text_auto= '.2s', animation_frame='year', range_y=[0,1000000000], height=1000)
fig.show()
df.info
df.groupby(['country']).sum()
| year | lifeExp | pop | gdpPercap | iso_num | |
|---|---|---|---|---|---|
| country | |||||
| Afghanistan | 23754 | 449.746 | 189884585 | 9632.095181 | 48 |
| Albania | 23754 | 821.195 | 30962990 | 39064.399592 | 96 |
| Algeria | 23754 | 708.362 | 238504874 | 53112.311678 | 144 |
| Angola | 23754 | 454.602 | 87712681 | 43285.206346 | 288 |
| Argentina | 23754 | 828.725 | 343226879 | 107466.645392 | 384 |
| ... | ... | ... | ... | ... | ... |
| Vietnam | 23754 | 689.754 | 654822851 | 12212.551382 | 8448 |
| West Bank and Gaza | 23754 | 723.944 | 22183278 | 45119.961375 | 3300 |
| Yemen, Rep. | 23754 | 561.365 | 130118302 | 18831.296066 | 10644 |
| Zambia | 23754 | 551.956 | 76245658 | 16298.392908 | 10728 |
| Zimbabwe | 23754 | 631.958 | 91703593 | 7630.296508 | 8592 |
142 rows × 5 columns
# YOUR CODE HERE
df_new = df.groupby(['year','country']).sum().reset_index()
fig = px.bar(df_new, x='country', y='pop', color= 'country', text_auto= '.2s', animation_frame='year', range_y=[0,1000000000], height=1000)
fig.update_xaxes(categoryorder='total ascending')
fig.update_xaxes(range=(131.5, 141.5))
fig.show()